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e24089 Background: Little is known about risk and protective factors for dementia in cancer survivors. With increasing longevity due to improved cancer therapy, it’s prudent to study factors contributing to cognitive impairment in this patient population. Methods: We performed multivariable cox regression analyses to assess established risk factors for all-cause dementia (age, education, APOE4-status, social and physical activity engagement) in breast and prostate cancer survivors. Patients 50+ years old with pathology-confirmed cancer diagnosis at Mayo Clinic were identified from a longitudinal, population-based cohort – Mayo Clinic Study of Aging. Analyses were controlled for age, APOE4-status, education, and cancer treatment. Results: We included a total of 209 patients with breast cancer (mean age 75.4 years, 24% APOE4-positive, median follow-up 6.8 years) and 352 with prostate cancer (mean age 77 years, 26% APOE4-positive, median follow-up 6.4 years). 31 patients with breast cancer (15%) and 66 patients with prostate cancer (20%) were diagnosed with dementia at last follow-up. Older age was associated with increased risk for dementia (5-year increase – breast: hazard ratio (HR) 1.9 [95%CI 1.3-2.7, p = 0.001]; prostate: HR 2.4 [95%CI 1.8-3.2, p < 0.0001]). APOE4-positivity was associated with increased dementia risk in breast (HR 3.6 [95%CI 1.6-7.8, p < 0.002]), but not prostate cancer (HR 1.2 [95%CI 0.7-2.0, p = 0.5]). More education was associated with lower dementia risk in prostate cancer (education year: HR 0.91 [95%CI 0.84-0.98, p < 0.02]; education years > 12: HR 0.26 [95%CI 0.1-0.6, p < 0.001]). Physical activity engagement in mid-life was associated with lower dementia risk (prostate: HR 0.56 [95%CI 0.4-0.8, p < 0.005]; breast: HR 0.48 [95%CI 0.3-0.9, p < 0.02]). Conclusions: In this longitudinal, population-based study we found that some risk and protective factors for dementia in cancer survivors vary by cancer type. While advanced age is an expected dementia risk factor, there were mixed results for APOE4-positivity (increased risk only in breast cancer) and education (only protective in prostate cancer). Our results support further study into factors influencing dementia risk by cancer type in hopes of identifying preventative strategies.

Abstract Blood-based biomarkers offer strong potential to revolutionize diagnosis, trial enrolment and treatment monitoring in Alzheimer’s disease (AD). However, further advances are needed before these biomarkers can achieve wider deployment beyond selective research studies and specialty memory clinics, including the development of frameworks for optimal interpretation of biomarker profiles. We hypothesized that integrating Alzheimer’s disease genetic risk score (AD-GRS) data would enhance the diagnostic value of plasma AD biomarkers by better capturing extant disease heterogeneity. Analysing 962 individuals from a population-based sample, we observed that an AD-GRS was independently associated with amyloid PET levels (an early marker of AD pathophysiology) over and above APOE ε4 or plasma p-tau181, amyloid-β42/40, glial fibrillary acidic protein or neurofilament light chain. Among individuals with a high or moderately high plasma p-tau181, integrating AD-GRS data significantly improved classification accuracy of amyloid PET positivity, including the finding that the combination of a high AD-GRS and high plasma p-tau181 outperformed p-tau181 alone in classifying amyloid PET positivity (88% versus 68%; P = 0.001). A machine learning approach incorporating plasma biomarkers, demographics and the AD-GRS was highly accurate in predicting amyloid PET levels (90% training set; 89% test set) and Shapley value analyses (an explainer method based in cooperative game theory) indicated that the AD-GRS and plasma biomarkers had differential importance in explaining amyloid deposition across individuals. Polygenic risk for AD dementia appears to account for a unique portion of disease heterogeneity, which could non-invasively enhance the interpretation of blood-based AD biomarker profiles in the population.